# ncnn-android-yolox

**Repository Path**: atari/ncnn-android-yolox

## Basic Information

- **Project Name**: ncnn-android-yolox
- **Description**: 同步 https://github.com/FeiGeChuanShu/ncnn-android-yolox
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2021-07-20
- **Last Updated**: 2021-11-11

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


The yolox object detection

This is a sample ncnn android project, it depends on ncnn library and opencv

https://github.com/Tencent/ncnn

https://github.com/nihui/opencv-mobile


## how to build and run
### step1
https://github.com/Tencent/ncnn/releases

* Download ncnn-YYYYMMDD-android-vulkan.zip or build ncnn for android yourself
* Extract ncnn-YYYYMMDD-android-vulkan.zip into **app/src/main/jni** and change the **ncnn_DIR** path to yours in **app/src/main/jni/CMakeLists.txt**

### step2
https://github.com/nihui/opencv-mobile

* Download opencv-mobile-XYZ-android.zip
* Extract opencv-mobile-XYZ-android.zip into **app/src/main/jni** and change the **OpenCV_DIR** path to yours in **app/src/main/jni/CMakeLists.txt**

### step3
* Open this project with Android Studio, build it and enjoy!

## some notes
* Android ndk camera is used for best efficiency
* Crash may happen on very old devices for lacking HAL3 camera interface
* All models are manually modified to accept dynamic input shape
* Most small models run slower on GPU than on CPU, this is common
* FPS may be lower in dark environment because of longer camera exposure time

## screenshot
![](screenshot.png)

## reference  
https://github.com/nihui/ncnn-android-nanodet  
https://github.com/Megvii-BaseDetection/YOLOX